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Data Freshness Analytics: String Normalisation + Secondary-Measure Weighted Mean
x402
Data Freshness Analytics: String Normalisation + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).
Computes string normalisation and secondary-measure weighted mean analytics on data freshness records (age_minutes, record_count) for up to 200 rows, returning 2 independent reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data freshness — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied data freshness records (age_minutes, record_count). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns 2 independent analytical reports: (1) a string normalisation report and (2) a secondary-measure weighted mean report, computed from the supplied data freshness rows (age_minutes and record_count values) — all processed locally with no external lookups or predictions.
Example use cases
Pipeline freshness audit by group
“I have 50 data freshness records with age_minutes and record_count across two dataset groups — can you run string normalisation and weighted mean reports on the age_minutes field so I can see how stale each group's data is?”
Record count weighted mean across dates
“Analyse these 120 data freshness rows for me: compute the string normalisation and secondary-measure weighted mean on record_count, grouped by dataset_group and date, so I can spot which groups have the heaviest recent load.”
Data quality baseline for monitoring
“I need two analytical reports — string normalisation and a weighted mean on age_minutes — for this batch of 80 freshness records spread across groups 'prod' and 'staging' to establish a data quality baseline.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-06-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, self-contained string normalisation and weighted mean analytics on data freshness records (age_minutes, record_count) without any external lookup, live data fetch, or prediction. Ideal for batch analytical reporting on up to 200 rows where two independent reports are needed in a single low-cost ($0.01 USDC) call.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, age_minutes, record_count) causes rejection
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Null values in both age_minutes and record_count simultaneously may produce incomplete statistics
- minItems:1 violation if empty array is submitted
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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